{"ID":2828950,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.13293","arxiv_id":"2512.13293","title":"Intrinsic-Motivation Multi-Robot Social Formation Navigation with Coordinated Exploration","abstract":"This paper investigates the application of reinforcement learning (RL) to multi-robot social formation navigation, a critical capability for enabling seamless human-robot coexistence. While RL offers a promising paradigm, the inherent unpredictability and often uncooperative dynamics of pedestrian behavior pose substantial challenges, particularly concerning the efficiency of coordinated exploration among robots. To address this, we propose a novel coordinated-exploration multi-robot RL algorithm introducing an intrinsic motivation exploration. Its core component is a self-learning intrinsic reward mechanism designed to collectively alleviate policy conservatism. Moreover, this algorithm incorporates a dual-sampling mode within the centralized training and decentralized execution framework to enhance the representation of both the navigation policy and the intrinsic reward, leveraging a two-time-scale update rule to decouple parameter updates. Empirical results on social formation navigation benchmarks demonstrate the proposed algorithm's superior performance over existing state-of-the-art methods across crucial metrics. Our code and video demos are available at: https://github.com/czxhunzi/CEMRRL.","short_abstract":"This paper investigates the application of reinforcement learning (RL) to multi-robot social formation navigation, a critical capability for enabling seamless human-robot coexistence. While RL offers a promising paradigm, the inherent unpredictability and often uncooperative dynamics of pedestrian behavior pose substan...","url_abs":"https://arxiv.org/abs/2512.13293","url_pdf":"https://arxiv.org/pdf/2512.13293v2","authors":"[\"Hao Fu\",\"Wei Liu\",\"Shuai Zhou\"]","published":"2025-12-15T13:03:08Z","proceeding":"cs.RO","tasks":"[\"cs.RO\",\"cs.AI\"]","methods":"[\"Reinforcement Learning\",\"LoRA\"]","has_code":false,"code_links":[{"ID":605916,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2828950,"paper_url":"https://arxiv.org/abs/2512.13293","paper_title":"Intrinsic-Motivation Multi-Robot Social Formation Navigation with Coordinated Exploration","repo_url":"https://github.com/czxhunzi/CEMRRL","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}